What Happened to Participation? Urban Development and Authoritarian Upgrading in Cairo's Informal Neighbourhoods

Participation appeared in development discourses for the first time in the 1970s, as a generic call for the involvement of the poor in development initiatives. Over the last three decades, the initial perspectives on participation intended as a project method for poverty reduction have evolved into a coherent and articulated theoretical elaboration, in which participation figures among the paraphernalia of good governance promotion: participation has acquired the status of “new orthodoxy”. Nevertheless, the experience of the implementation of participatory approaches in development projects seemed to be in the majority of cases rather disappointing, since the transformative potential of ‘participation in development’ depends on a series of factors in which every project can actually differ from others: the ultimate aim of the approach promoted, its forms and contents and, last but not least, the socio-political context in which the participatory initiative is embedded. In Egypt, the signature of a project agreement between the Arab Republic of Egypt and the Federal Republic of Germany, in 1998, inaugurated a Participatory Urban Management Programme (PUMP) to be implemented in Greater Cairo by the German Technical Cooperation (Deutsche Gesellschaft für Technische Zusammenarbeit, GTZ) and the Ministry of Planning (now Ministry of Local Development) and the Governorates of Giza and Cairo as the main counterparts. Now, ten years after the beginning of the PUMP/PDP and close to its end (December 2010), it is possible to draw some conclusions about the scope, the significance and the effects of the participatory approach adopted by GTZ and appropriated by the Egyptian counterparts in dealing with the issue of informal areas and, more generally, of urban development. Our analysis follows three sets of questions: the first set regards the way ‘participation’ has been interpreted and concretised by PUMP and PDP. The second is about the emancipating potential of the ‘participatory approach’ and its ability to ‘empower’ the ‘marginalised’. The third focuses on one hand on the efficacy of GTZ strategy to lead to an improvement of the delivery service in informal areas (especially in terms of planning and policies), and on the other hand on the potential of GTZ development intervention to trigger an incremental process of ‘democratisation’ from below.

Learning for scheduling a portfolio of constraint solvers

Nel lavoro di tesi qui presentato si indaga l'applicazione di tecniche di apprendimento mirate ad una più efficiente esecuzione di un portfolio di risolutore di vincoli (constraint solver). Un constraint solver è un programma che dato in input un problema di vincoli, elabora una soluzione mediante l'utilizzo di svariate tecniche. I problemi di vincoli sono altamente presenti nella vita reale. Esempi come l'organizzazione dei viaggi dei treni oppure la programmazione degli equipaggi di una compagnia aerea, sono tutti problemi di vincoli. Un problema di vincoli è formalizzato da un problema di soddisfacimento di vincoli(CSP). Un CSP è descritto da un insieme di variabili che possono assumere valori appartenenti ad uno specico dominio ed un insieme di vincoli che mettono in relazione variabili e valori assumibili da esse. Una tecnica per ottimizzare la risoluzione di tali problemi è quella suggerita da un approccio a portfolio. Tale tecnica, usata anche in am- biti come quelli economici, prevede la combinazione di più solver i quali assieme possono generare risultati migliori di un approccio a singolo solver. In questo lavoro ci preoccupiamo di creare una nuova tecnica che combina un portfolio di constraint solver con tecniche di machine learning. Il machine learning è un campo di intelligenza articiale che si pone l'obiettivo di immettere nelle macchine una sorta di `intelligenza'. Un esempio applicativo potrebbe essere quello di valutare i casi passati di un problema ed usarli in futuro per fare scelte. Tale processo è riscontrato anche a livello cognitivo umano. Nello specico, vogliamo ragionare in termini di classicazione. Una classicazione corrisponde ad assegnare ad un insieme di caratteristiche in input, un valore discreto in output, come vero o falso se una mail è classicata come spam o meno. La fase di apprendimento sarà svolta utilizzando una parte di CPHydra, un portfolio di constraint solver sviluppato presso la University College of Cork (UCC). Di tale algoritmo a portfolio verranno utilizzate solamente le caratteristiche usate per descrivere determinati aspetti di un CSP rispetto ad un altro; queste caratteristiche vengono altresì dette features. Creeremo quindi una serie di classicatori basati sullo specifico comportamento dei solver. La combinazione di tali classicatori con l'approccio a portfolio sara nalizzata allo scopo di valutare che le feature di CPHydra siano buone e che i classicatori basati su tali feature siano affidabili. Per giusticare il primo risultato, eettueremo un confronto con uno dei migliori portfolio allo stato dell'arte, SATzilla. Una volta stabilita la bontà delle features utilizzate per le classicazioni, andremo a risolvere i problemi simulando uno scheduler. Tali simulazioni testeranno diverse regole costruite con classicatori precedentemente introdotti. Prima agiremo su uno scenario ad un processore e successivamente ci espanderemo ad uno scenario multi processore. In questi esperimenti andremo a vericare che, le prestazioni ottenute tramite l'applicazione delle regole create appositamente sui classicatori, abbiano risultati migliori rispetto ad un'esecuzione limitata all'utilizzo del migliore solver del portfolio. I lavoro di tesi è stato svolto in collaborazione con il centro di ricerca 4C presso University College Cork. Su questo lavoro è stato elaborato e sottomesso un articolo scientico alla International Joint Conference of Articial Intelligence (IJCAI) 2011. Al momento della consegna della tesi non siamo ancora stati informati dell'accettazione di tale articolo. Comunque, le risposte dei revisori hanno indicato che tale metodo presentato risulta interessante.

A study on set variable representations in constraint programming

Il lavoro presentato in questa tesi si colloca nel contesto della programmazione con vincoli, un paradigma per modellare e risolvere problemi di ricerca combinatoria che richiedono di trovare soluzioni in presenza di vincoli. Una vasta parte di questi problemi trova naturale formulazione attraverso il linguaggio delle variabili insiemistiche. Dal momento che il dominio di tali variabili può essere esponenziale nel numero di elementi, una rappresentazione esplicita è spesso non praticabile. Recenti studi si sono quindi focalizzati nel trovare modi efficienti per rappresentare tali variabili. Pertanto si è soliti rappresentare questi domini mediante l'uso di approssimazioni definite tramite intervalli (d'ora in poi rappresentazioni), specificati da un limite inferiore e un limite superiore secondo un'appropriata relazione d'ordine. La recente evoluzione della ricerca sulla programmazione con vincoli sugli insiemi ha chiaramente indicato che la combinazione di diverse rappresentazioni permette di raggiungere prestazioni di ordini di grandezza superiori rispetto alle tradizionali tecniche di codifica. Numerose proposte sono state fatte volgendosi in questa direzione. Questi lavori si differenziano su come è mantenuta la coerenza tra le diverse rappresentazioni e su come i vincoli vengono propagati al fine di ridurre lo spazio di ricerca. Sfortunatamente non esiste alcun strumento formale per paragonare queste combinazioni. Il principale obiettivo di questo lavoro è quello di fornire tale strumento, nel quale definiamo precisamente la nozione di combinazione di rappresentazioni facendo emergere gli aspetti comuni che hanno caratterizzato i lavori precedenti. In particolare identifichiamo due tipi possibili di combinazioni, una forte ed una debole, definendo le nozioni di coerenza agli estremi sui vincoli e sincronizzazione tra rappresentazioni. Il nostro studio propone alcune interessanti intuizioni sulle combinazioni esistenti, evidenziandone i limiti e svelando alcune sorprese. Inoltre forniamo un'analisi di complessità della sincronizzazione tra minlex, una rappresentazione in grado di propagare in maniera ottimale vincoli lessicografici, e le principali rappresentazioni esistenti.

Hybrid constraint programming and metaheuristic methods for large scale optimization problems

This work presents hybrid Constraint Programming (CP) and metaheuristic methods for the solution of Large Scale Optimization Problems; it aims at integrating concepts and mechanisms from the metaheuristic methods to a CP-based tree search environment in order to exploit the advantages of both approaches. The modeling and solution of large scale combinatorial optimization problem is a topic which has arisen the interest of many researcherers in the Operations Research field; combinatorial optimization problems are widely spread in everyday life and the need of solving difficult problems is more and more urgent. Metaheuristic techniques have been developed in the last decades to effectively handle the approximate solution of combinatorial optimization problems; we will examine metaheuristics in detail, focusing on the common aspects of different techniques. Each metaheuristic approach possesses its own peculiarities in designing and guiding the solution process; our work aims at recognizing components which can be extracted from metaheuristic methods and re-used in different contexts. In particular we focus on the possibility of porting metaheuristic elements to constraint programming based environments, as constraint programming is able to deal with feasibility issues of optimization problems in a very effective manner. Moreover, CP offers a general paradigm which allows to easily model any type of problem and solve it with a problem-independent framework, differently from local search and metaheuristic methods which are highly problem specific. In this work we describe the implementation of the Local Branching framework, originally developed for Mixed Integer Programming, in a CP-based environment. Constraint programming specific features are used to ease the search process, still mantaining an absolute generality of the approach. We also propose a search strategy called Sliced Neighborhood Search, SNS, that iteratively explores slices of large neighborhoods of an incumbent solution by performing CP-based tree search and encloses concepts from metaheuristic techniques. SNS can be used as a stand alone search strategy, but it can alternatively be embedded in existing strategies as intensification and diversification mechanism. In particular we show its integration within the CP-based local branching. We provide an extensive experimental evaluation of the proposed approaches on instances of the Asymmetric Traveling Salesman Problem and of the Asymmetric Traveling Salesman Problem with Time Windows. The proposed approaches achieve good results on practical size problem, thus demonstrating the benefit of integrating metaheuristic concepts in CP-based frameworks.

Constraint based methods for allocation and scheduling of periodic applications

This work presents exact algorithms for the Resource Allocation and Cyclic Scheduling Problems (RA&CSPs). Cyclic Scheduling Problems arise in a number of application areas, such as in hoist scheduling, mass production, compiler design (implementing scheduling loops on parallel architectures), software pipelining, and in embedded system design. The RA&CS problem concerns time and resource assignment to a set of activities, to be indefinitely repeated, subject to precedence and resource capacity constraints. In this work we present two constraint programming frameworks facing two different types of cyclic problems. In first instance, we consider the disjunctive RA&CSP, where the allocation problem considers unary resources. Instances are described through the Synchronous Data-flow (SDF) Model of Computation. The key problem of finding a maximum-throughput allocation and scheduling of Synchronous Data-Flow graphs onto a multi-core architecture is NP-hard and has been traditionally solved by means of heuristic (incomplete) algorithms. We propose an exact (complete) algorithm for the computation of a maximum-throughput mapping of applications specified as SDFG onto multi-core architectures. Results show that the approach can handle realistic instances in terms of size and complexity. Next, we tackle the Cyclic Resource-Constrained Scheduling Problem (i.e. CRCSP). We propose a Constraint Programming approach based on modular arithmetic: in particular, we introduce a modular precedence constraint and a global cumulative constraint along with their filtering algorithms. Many traditional approaches to cyclic scheduling operate by fixing the period value and then solving a linear problem in a generate-and-test fashion. Conversely, our technique is based on a non-linear model and tackles the problem as a whole: the period value is inferred from the scheduling decisions. The proposed approaches have been tested on a number of non-trivial synthetic instances and on a set of realistic industrial instances achieving good results on practical size problem.

The Road to Poverty Reduction: Corporate Governance and Female Participation in MFIs

1.Microfinance Industry – Context of Analysis. This paper is an introduction to the microfinance industry. It serves as a context of analysis, for the empirical settings and basis for building the theoretical argument for the thesis. 2.Women in Microfinance Institutions: The Road to Poverty Reduction and Gender Equality? One of the unique aspects of microfinance institutions is their focus on outreach, i.e. their ability to reach the poor. This paper explores whether the presence of women in microfinance institutions is associated with improved outreach. Building on prior research that shows that women tend to improve financial performance and social responsibility, we examine an original dataset of 226 microfinance institutions. The empirical results suggest that the presence of a female CEO, female managers and female loan officers is directly related to improved outreach, while the presence of women board members is not. 3. Women in Microfinance Institutions: Is There a Trade-Off Between Outreach and Sustainability? Abstract This paper’s contribution to the understanding of microfinance is two-fold. First, while it has been shown that female CEOs in MFIs increase financial performance, it will be argued that female managers, female loan officers and female board members will do the same. Secondly, having previously shown that having a female presence in management in MFIs improves social performance the outreach, it will be argued that having females in the MFIs’ management will not lead to a trade-off between outreach and sustainability. These findings are based on an original data set of 226 MFIs. Statistical analysis demonstrates that a weak relationship between female managers and female loan officers vis-à-vis financial performance, but female board members do not. The trade-off between outreach and sustainability can be avoided with the appointment of females to the MFIs’ management positions, but the same cannot be concluded for female board members.

Portfolio Approaches in Constraint Programming

Recent research has shown that the performance of a single, arbitrarily efficient algorithm can be significantly outperformed by using a portfolio of —possibly on-average slower— algorithms. Within the Constraint Programming (CP) context, a portfolio solver can be seen as a particular constraint solver that exploits the synergy between the constituent solvers of its portfolio for predicting which is (or which are) the best solver(s) to run for solving a new, unseen instance. In this thesis we examine the benefits of portfolio solvers in CP. Despite portfolio approaches have been extensively studied for Boolean Satisfiability (SAT) problems, in the more general CP field these techniques have been only marginally studied and used. We conducted this work through the investigation, the analysis and the construction of several portfolio approaches for solving both satisfaction and optimization problems. We focused in particular on sequential approaches, i.e., single-threaded portfolio solvers always running on the same core. We started from a first empirical evaluation on portfolio approaches for solving Constraint Satisfaction Problems (CSPs), and then we improved on it by introducing new data, solvers, features, algorithms, and tools. Afterwards, we addressed the more general Constraint Optimization Problems (COPs) by implementing and testing a number of models for dealing with COP portfolio solvers. Finally, we have come full circle by developing sunny-cp: a sequential CP portfolio solver that turned out to be competitive also in the MiniZinc Challenge, the reference competition for CP solvers.

The role of indigenous people in national development processes: Participation and marginalisation of indigenous Bedouin in South Sinai tourism development

The Bedouin of South Sinai have been significantly affected by the politics of external powers for a long time. However, never had the interest of external powers in Sinai been so strong as since the Israeli-Egyptian wars in the second half of the 20th century when Bedouin interests started to collide with Egypt’s plans for a development of luxury tourism in South Sinai. rnrnThe tourism boom that has started in the 1980s has brought economic and infrastructure development to the Bedouin and tourism has become the most important source of income for the Bedouin. However, while the absolute increase of tourists to Sinai has trickled down to the Bedouin to some extent, the participation of Bedouin in the overall tourism development is under-proportionate. Moreover, the Bedouin have become increasingly dependent on monetary income and consequently from tourism as the only significant source of income while at the same time they have lost much of their land as well as their self-determination.rnrnIn this context, the Bedouin livelihoods have become very vulnerable due to repeated depressions in the tourism industry as well as marginalization. Major marginalization processes the Bedouin are facing are the loss of land, barriers to market entry, especially increasingly strict rules and regulations in the tourism industry, as well as discrimination by the authorities. Social differentiation and Bedouin preferences are identified as further factors in Bedouin marginalization.rnrnThe strategies Bedouin have developed in response to all these problems are coping strategies, which try to deal with the present problem at the individual level. Basically no strategies have been developed at the collective level that would aim to actively shape the Bedouin’s present and future. Collective action has been hampered by a variety of factors, such as the speed of the developments, the distribution of power or the decay of tribal structures.rnWhile some Bedouin might be able to continue their tourism activities, a large number of informal jobs will not be feasible anymore. The majority of the previously mostly self-employed Bedouin will probably be forced to work as day-laborers who will have lost much of their pride, dignity, sovereignty and freedom. Moreover, with a return to subsistence being impossible for the majority of the Bedouin, it is likely that an increasing number of marginalized Bedouin will turn to illegal income generating activities such as smuggling or drug cultivation. This in turn will lead to further repression and discrimination and could escalate in a serious violent conflict between the Bedouin and the government.rnrnDevelopment plans and projects should address the general lack of civil rights, local participation and protection of minorities in Egypt and promote Bedouin community development and the consideration of Bedouin interests in tourism development.rnrnWether the political upheavals and the resignation of president Mubarak at the beginning of 2011 will have a positive effect on the situation of the Bedouin remains to be seen.rn

The association between extra-curricular sport participation and social anxiety symptoms in children

Social anxiety is a common psychological complaint that can have a significant and long-term negative impact on a child’s social and cognitive development. In the current study, the relationship between sport participation and social anxiety symptoms was investigated. Swiss primary school children (N = 201), parents, and teachers provided information about the children’s social anxiety symptoms, classroom behavior, and sport involvement. Gender differences were observed on social anxiety scores, where girls tended to report higher social anxiety symptoms, as well as on sport activity, where boys engaged in more sport involvement. MANCOVAs with gender as covariant showed no differences in social anxiety symptoms between children involved in an extracurricular sport and those not engaged in sport participation. Nevertheless, children engaged in team sports displayed fewer physical social anxiety symptoms than children involved in individual sports.

Development of Dynamic Constraint Models for a Model Based Transient Calibration Process

Model based calibration has gained popularity in recent years as a method to optimize increasingly complex engine systems. However virtually all model based techniques are applied to steady state calibration. Transient calibration is by and large an emerging technology. An important piece of any transient calibration process is the ability to constrain the optimizer to treat the problem as a dynamic one and not as a quasi-static process. The optimized air-handling parameters corresponding to any instant of time must be achievable in a transient sense; this in turn depends on the trajectory of the same parameters over previous time instances. In this work dynamic constraint models have been proposed to translate commanded to actually achieved air-handling parameters. These models enable the optimization to be realistic in a transient sense. The air handling system has been treated as a linear second order system with PD control. Parameters for this second order system have been extracted from real transient data. The model has been shown to be the best choice relative to a list of appropriate candidates such as neural networks and first order models. The selected second order model was used in conjunction with transient emission models to predict emissions over the FTP cycle. It has been shown that emission predictions based on air-handing parameters predicted by the dynamic constraint model do not differ significantly from corresponding emissions based on measured air-handling parameters.